An Effective Information Theoretic Framework for Channel Pruning

14 August 2024

Papers citing "An Effective Information Theoretic Framework for Channel Pruning"

8 / 8 papers shown

Title
Mix-QSAM: Mixed-Precision Quantization of the Segment Anything Model Navin Ranjan Andreas E. Savakis MQ VLM 61 0 0 08 May 2025
SGLP: A Similarity Guided Fast Layer Partition Pruning for Compressing Large Deep Models Yuqi Li Yao Lu Zeyu Dong Chuanguang Yang Yihao Chen Jianping Gou 16 2 0 14 Oct 2024
Carrying out CNN Channel Pruning in a White Box Yu-xin Zhang Mingbao Lin Chia-Wen Lin Jie Chen Feiyue Huang Yongjian Wu Yonghong Tian R. Ji VLM 26 58 0 24 Apr 2021
Feature Pyramid Networks for Object Detection Tsung-Yi Lin Piotr Dollár Ross B. Girshick Kaiming He Bharath Hariharan Serge J. Belongie ObjD 166 21,643 0 09 Dec 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 244 35,884 0 25 Aug 2016
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 420 15,438 0 02 Nov 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 229 74,467 0 18 May 2015
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 279 39,083 0 01 Sep 2014